SegImage
所属分类：图形图像处理
开发工具：Visual C++
文件大小：738KB
下载次数：47
上传日期：2007-02-05 20:45:58
上 传 者：
kinghong
说明： 很好的图象分割算法,有测试程序和测试例子
(good image segmentation algorithm, test procedures and test case)
文件列表:
248079\SegImage\SegImage\Makefile (338, 2005-02-23)
248079\SegImage\SegImage\convolve.h (1219, 2005-02-23)
248079\SegImage\SegImage\disjoint-set.h (1153, 2006-05-30)
248079\SegImage\SegImage\filter.h (2252, 2005-02-23)
248079\SegImage\SegImage\image.h (1573, 2005-02-23)
248079\SegImage\SegImage\imconv.h (4205, 2005-02-23)
248079\SegImage\SegImage\imutil.h (927, 2005-02-23)
248079\SegImage\SegImage\misc.h (1010, 2005-02-23)
248079\SegImage\SegImage\pnmfile.h (4532, 2005-02-23)
248079\SegImage\SegImage\segment-graph.h (1449, 2006-05-30)
248079\SegImage\SegImage\segment-image.h (3582, 2006-05-30)
248079\SegImage\SegImage\segment.cpp (742, 2006-05-28)
248079\SegImage\SegImage\SegImage.vcproj (3707, 2006-05-28)
248079\SegImage\SegImage.sln (889, 2006-05-28)
248079\SegImage\SegImage.ncb (1739776, 2006-05-30)
248079\SegImage\SegImage\.DS_Store (6148, 2005-06-08)
248079\SegImage\SegImage.suo (14336, 2006-05-30)
248079\SegImage\SegImage\SegImage.vcproj.KELVINYE.HongJing.user (1413, 2006-05-30)
248079\SegImage\SegImage\Debug (0, 2006-05-29)
248079\SegImage\SegImage (0, 2006-05-30)
248079\SegImage\debug (0, 2006-05-30)
248079\SegImage (0, 2006-05-29)
248079 (0, 2011-02-18)
Implementation of the segmentation algorithm described in:
Efficient Graph-Based Image Segmentation
Pedro F. Felzenszwalb and Daniel P. Huttenlocher
International Journal of Computer Vision, 59(2) September 2004.
The program takes a color image (PPM format) and produces a segmentation
with a random color assigned to each region.
1) Type "make" to compile "segment".
2) Run "segment sigma k min input output".
The parameters are: (see the paper for details)
sigma: Used to smooth the input image before segmenting it.
k: Value for the threshold function.
min: Minimum component size enforced by post-processing.
input: Input image.
output: Output image.
Typical parameters are sigma = 0.5, k = 500, min = 20.
Larger values for k result in larger components in the result.
近期下载者：
相关文件：
收藏者：